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Exploring Unsupervised Machine Learning Techniques for Genomic Island Categorization

Authors:

Noushin Ghaffari,

Lijie Zhou,

Catherine Mageeney,

Kelly Porter WilliamsAuthors Info & Claims

PEARC '23: Practice and Experience in Advanced Research Computing 2023: Computing for the Common Good

Pages 445 - 447

https://doi.org/10.1145/3569951.3597563

Published: 10 September 2023 Publication History

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References

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Daniel M. de Brito,Vinicius Maracaja-Coutinho,Savio T. de Farias,Leonardo V. Batista,Thaís G. do Rêgo. 2016. A Novel Method to Predict Genomic Islands Based on Mean Shift Clustering Algorithm. PLOS ONE. https://doi.org/10.1371/journal.pone.0146352

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PEARC '23: Practice and Experience in Advanced Research Computing 2023: Computing for the Common Good

July 2023

519 pages

ISBN:9781450399852

DOI:10.1145/3569951

Editors:
Robert Sinkovits
San Diego Supercomputer Center
,
Alana Romanella
University of Colorado Boulder
,
Shelley Knuth
University of Colorado Boulder
,
Ken Hackworth
Pittsburgh Supercomputing Center
,
Jeff Pummill
University of Arkansas

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 10 September 2023

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sRNA associated genomic islands in Salmonella spp.

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sRNA associated genomic islands in Salmonella spp.

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Could n-gram analysis contribute to genomic island determination?

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